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Detaljer för kursplan för kurs FMA285F giltig från och med HT 2025

Utskriftsvänlig visning

Allmänt
Syfte
  • On completion of the course, participants shall be able to:
    • Describe modern algorithms for minimization of a convex functional, such as e.g. FBS, Dykstra, Douglas-Rachford, ADMM, Chambolle-Pock, and get an overview of pros and cons as well as different areas of application, for each respective algorithm.
    • Be able to clarify under which circumstances the above algorithms converge, and in basic terms understand the underlying proof.
    • Understand how minimization problems can be reformulated in terms of maximally monotone operators, and its connection to various fixpoint theorems.
    • Understand how duality and the Fenchel transform is used to reformulate minimization problems.
    • Clarify basic properties of convex functions and its connections to lower semicontinuous functions and subdifferential calculus.
    • Understand the role of proximal operators for convex optimization routines.
Innehåll
  • Theory for classes of non-expansive operators, fixpoint iterations, Fejer monotinicity, Krasnoelskii-Mann’s theorem. Classes of convex functions and their properties, semicontinuous functions. The Fenchel-transform and convex hulls, the Fenchel-Moreau theorem. Subdifferentiability of convex funktions. Monotone operators and proximal operators. Convergence theorems for known algorithms such as those mentioned above.
Kunskap och förståelse
  • För godkänd kurs skall doktoranden
  • Describe modern algorithms for minimization of a convex functional, such as e.g. FBS, Dykstra, Douglas-Rachford, ADMM, Chambolle-Pock, and get an overview of pros and cons as well as different areas of application, for each respective algorithm.

    Understand how duality and the Fenchel transform is used to reformulate minimization problems.

    Clarify basic properties of convex functions and its connections to lower semicontinuous functions and subdifferential calculus.

    Understand the role of proximal operators for convex optimization routines.
Färdighet och förmåga
  • För godkänd kurs skall doktoranden
  • Determine under which circumstances the above algorithms converge, and in basic terms understand the underlying proof.

    Determine when minimization problems can be reformulated in terms of maximally monotone operators, and its connection to various fixpoint theorems.
Värderingsförmåga och förhållningssätt
  • För godkänd kurs skall doktoranden
Undervisningsformer
  • Föreläsningar
  • Seminarier
  • övrigt
  • Self studies followed by presentations of the material by the students.
Examinationsformer
  • Muntlig tentamen
  • övrigt
  • Presentations by the students
  • Underkänd, godkänd
Förkunskapskrav
  • Functional analysis MATP15 or equivalent
Förutsatta förkunskaper
Urvalskriterier
Litteratur
  • Heinz H. Bauschke, Patrick L. Combettes: Convex Analysis and Monotone Operator Theory in Hilbert Spaces. Springer.
Övrig information
Kurskod
  • FMA285F
Administrativ information
  • 2025-06-16
  • Maria Sandsten

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Utskriftsvänlig visning